The present invention relates to the field of information processing technology. More specifically, to a technology that more precisely detects negative opinions in social media regarding an organization, a product, a service, or an individual.
Since an enormous number of messages are exchanged in social media, a situation can arise in which criticism about a certain topic is spread in a short period of time, causing a flood of messages expressing negative opinions. When the target of such negative opinions is a company or its products, it is highly likely that such negative opinions will seriously damage the company's image and business. Accordingly, there is a business demand for grasping the emergence of negative opinions in social media at an early stage. In response to such a demand, various technical methods have been suggested in the related art.
An increase in the number of messages about a certain topic tends to occur in accordance with the novelty or impact of the topic. Examples of such an increase include a sharp increase in the number of messages about a new product when the release date is announced, when the product is released, or when an event related to the product is held; a sharp increase in the number of messages about public transportation after a disaster occurs; and a sharp increase in the number of messages about a certain news item. As a result of this sharp increase, it is difficult to grasp circulating information related to negative opinions by only monitoring an increasing trend in the number of messages about a certain topic.
Also, negative opinions are expressed in a great variety of ways and it is difficult to precisely detect all the negative opinions on the basis of a specific expression that is predefined (e.g., a keyword related to an offensive or inappropriate word). An example of this is as follows. After the Great East Japan Earthquake, planned blackouts in specific regions were scheduled due to an electric power shortage caused by suspended operations of nuclear power plants. In social media the fact that “only specific commercial facilities in a region of planned blackouts are not to be targets of planned blackouts” was criticized as being unfair. However, “not being a target of planned blackouts” is generally not criticized and is difficult to detect even by using an opinion analysis method (a technique of recognizing positive or negative opinions) which has been studied in recent years.
The present invention has been made in view of the above-mentioned problems. Improvements to related art are still desired to provide a more precise means for detecting a situation where something is criticized in social media (e.g., messages expressing negative opinions circulating in microblogs) and for grasping the details of the criticism.